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Investigation of unknown causes of uveal melanoma uncovers seven recurrent genetic mutations

Nanda et al. | Aug 25, 2022

Investigation of unknown causes of uveal melanoma uncovers seven recurrent genetic mutations

Uveal melanoma (UM) is a rare subtype of melanoma but the most frequent primary cancer of the eye in adults. The goal of this study was to research the genetic causes of UM through a comprehensive frequency analysis of base-pair mismatches in patient genomes. Results showed a total of 130 genetic mutations, including seven recurrent mutations, with most mutations occurring in chromosomes 3 and X. Recurrent mutations varied from 8.7% to 17.39% occurrence in the UM patient sample, with all mutations identified as missense. These findings suggest that UM is a recessive heterogeneous disease with selective homozygous mutations. Notably, this study has potential wider significance because the seven genes targeted by recurrent mutations are also involved in other cancers.

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Effect Of SMC On The Growth Of Bean, Cherry Tomato And Roma Tomato Plant

Rao et al. | Sep 12, 2020

Effect Of SMC On The Growth Of Bean, Cherry Tomato And Roma Tomato Plant

Mushroom compost, also called Spent Mushroom Substrate or Spent Mushroom Compost (SMC), is suitable for a variety of plants. Previous research has found that the application of SMC will increase plant growth. However, it is unclear which exact proportions of SMC and soil will maximize tomato and bean plant growth. We showed that the hypothesized growth media with 30% SMC optimizes seed germination, plant height, number of leaves, and survival rate compared to other combinations of growth media. Our research suggests that SMC is a useful alternative for conventional fertilizers.

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Evaluation of Tea Extract as an Inhibitor of Oxidative Stress in Prostate Cells

Zhang et al. | Jan 22, 2019

Evaluation of Tea Extract as an Inhibitor of Oxidative Stress in Prostate Cells

One important factor that contributes to human cancers is accumulated damage to cells' DNA due to the oxidative stress caused by free radicals. In this study, the authors investigate the effects of several different tea leaf extracts on oxidative stress in cultured human prostate cells to see if antioxidants in the tea leaves could help protect cells from this type of DNA damage. They found that all four types of tea extract (as well as direct application of the antioxidant EGCG) improved the outcomes for the cultured cells, with white tea extract having the strongest effect. This research suggests that tea extracts and the antioxidants that they contain may have applications in the treatment of the many diseases associated with cellular DNA damage, including cancer.

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Effect of Natural Compounds Curcumin and Nicotinamide on α-synuclein Accumulation in a C. elegans Model of Parkinson’s Disease

Mehrotra et al. | Jan 29, 2018

Effect of Natural Compounds Curcumin and Nicotinamide on α-synuclein Accumulation in a C. elegans Model of Parkinson’s Disease

Parkinson's disease is a neurodegenerative disorder that affects over 10 million people worldwide. It is caused by destruction of dopamine-producing neurons, which results in severe motor and movement symptoms. In this study, the authors investigated the anti-Parkinsonian effects of two natural compounds curcumin and nicotinamide using C. elegans as a model organism.

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Antibiotic Residues Detected in Commercial Cow’s Milk

Memili et al. | Mar 18, 2015

Antibiotic Residues Detected in Commercial Cow’s Milk

Antibiotics are oftentimes used to treat mastitis (infection of the mammary gland) in dairy cows. Regulations require that milk from these cows be discarded until the infection has cleared and antibiotic residues are no longer detectable in the cow's milk. These regulations are in place to protect consumers and to help prevent the rise of antibiotic resistant bacteria. In this study, the authors test milk samples from 10 milk suppliers in the Greensboro, NC to see if they contain detectable levels of antibiotic residues.

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Model selection and optimization for poverty prediction on household data from Cambodia

Wong et al. | Sep 29, 2023

Model selection and optimization for poverty prediction on household data from Cambodia
Image credit: Paul Szewczyk

Here the authors sought to use three machine learning models to predict poverty levels in Cambodia based on available household data. They found teat multilayer perceptron outperformed the other models, with an accuracy of 87 %. They suggest that data-driven approaches such as these could be used more effectively target and alleviate poverty.

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Antibacterial properties of household spices and toothpaste against oral bacteria

Toliver et al. | Apr 24, 2023

Antibacterial properties of household spices and toothpaste against oral bacteria

Bacteria cause tooth decay, plaque, bad breath, and other diseases. Despite being cleaned with water and toothpaste, oral bacteria live on our toothbrushes. Bacterial growth has been shown to be inhibited by different toothpastes and common household spices. This study tested how different toothpastes and common household spices, including cinnamon, cumin, nutmeg, and ground white pepper, can inhibit bacteria from growing on toothbrushes

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The Potential of Fibroblast Growth Factors to Stimulate Hair Growth In Vitro

Cheng et al. | Nov 07, 2021

The Potential of Fibroblast Growth Factors to Stimulate Hair Growth In Vitro

Identifying treatments that can stimulate hair growth use could help those struggling with undesirable hair loss. Here, the authors show that Fibroblast Growth Factors can stimulate the division of cells isolated from the mouse hair follicle. Their results suggest that this family of growth factors might be helpful in stimulating hair growth in living animals as well.

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